Triple
T28753922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida State Road 84 |
E731612
|
entity |
| Predicate | hasFormerDesignation |
P12531
|
FINISHED |
| Object | part of original Alligator Alley route |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: part of original Alligator Alley route | Statement: [Florida State Road 84, hasFormerDesignation, part of original Alligator Alley route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerDesignation Context triple: [Florida State Road 84, hasFormerDesignation, part of original Alligator Alley route]
-
A.
formerDesignation
chosen
Indicates that an entity previously held a particular title, role, or designation that it no longer holds.
-
B.
hasDesignation
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
C.
hasFormerTitle
Indicates that an entity previously held a specific title or position but no longer does.
-
D.
hasDesignationStatus
Indicates that an entity holds a particular official designation or status within a defined classification or recognition system.
-
E.
hasDesignationBy
Indicates that one entity has been formally assigned or labeled with a specific designation by another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f043ed68a881909e858a06bab7a247 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 28, 2026, 6:08 a.m.